通过语义引导弥合UI生成中的沟壑
Bridging Gulfs in UI Generation through Semantic Guidance
- Seoul National University（首尔国立大学）
机构由 AI 辅助整理，请以论文原文为准。
AI总结：
通过语义引导弥合UI生成中的执行与评估沟壑，提升用户对设计意图和结果的控制与理解。
AI中文摘要：
尽管生成式AI能够从文本提示生成高质量的用户界面（UI），但用户在表达设计意图和评估或改进结果时面临困难，导致执行沟壑和评估沟壑的产生。为了了解UI生成所需的信息，我们对UI提示指南进行了主题分析，确定了关键的设计语义，并发现它们是层次化且相互依赖的。基于这些发现，我们开发了一套系统，使用户能够指定语义、可视化关系，并提取语义如何反映在生成的UI中的方式。通过使语义成为人类意图和AI输出之间的中间表示，我们的系统通过使要求明确和结果可解释来弥合这两个沟壑。一项比较性用户研究表明，我们的方法增强了用户对意图表达和结果解释的感知控制，并促进了更加可预测的迭代改进。我们的工作展示了如何通过显式的语义表示系统地和可解释地探索AI驱动的UI设计的可能性。
英文摘要：
While generative AI enables high-fidelity UI generation from text prompts, users struggle to articulate design intent and evaluate or refine results-creating gulfs of execution and evaluation. To understand the information needed for UI generation, we conducted a thematic analysis of UI prompting guidelines, identifying key design semantics and discovering that they are hierarchical and interdependent. Leveraging these findings, we developed a system that enables users to specify semantics, visualize relationships, and extract how semantics are reflected in generated UIs. By making semantics serve as an intermediate representation between human intent and AI output, our system bridges both gulfs by making requirements explicit and outcomes interpretable. A comparative user study suggests that our approach enhances users' perceived control over intent expression and outcome interpretation, and facilitates more predictable iterative refinement. Our work demonstrates how explicit semantic representation enables systematic and explainable exploration of design possibilities in AI-driven UI design.
